Exploring chaos automata for protein sequences

Author

Stoffer, Deborah A. ; Volkert, L. Gwenn

Author_Institution

Dept. of Comput. Sci., Kent State Univ., Kent, OH

fYear

2008

fDate

15-17 Sept. 2008

Firstpage

38

Lastpage

45

Abstract

Fractals have been used to visually represent biological sequences since 1990. At first simple chaos games were used to generate fractal visualizations for DNA sequences, but the technique developed into using more complex systems to visually represent DNA and protein sequences. One of these more complex systems, termed chaos automata, combined iterated function systems with finite state automata to retain a memory of sequence input. The parameters for chaos automata were evolved by evolutionary algorithm to distinguish between different properties in DNA sequence input. Here, chaos automata have been extended to protein sequences and explored using synthetic protein sequence data.

Keywords

automata theory; bioinformatics; biological techniques; data visualisation; evolutionary computation; finite state machines; iterative methods; proteins; proteomics; DNA sequence input; DNA sequences; biological sequence visual representation; chaos automata; evolutionary algorithm; finite state automata; fractals; iterated function systems; protein sequences; sequence input memory; Automata; Chaos; DNA; Data visualization; Evolutionary computation; Fractals; Gaskets; Image generation; Protein engineering; Protein sequence;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Bioinformatics and Computational Biology, 2008. CIBCB '08. IEEE Symposium on

Conference_Location

Sun Valley, ID

Print_ISBN

978-1-4244-1778-0

Electronic_ISBN

978-1-4244-1779-7

Type

conf

DOI

10.1109/CIBCB.2008.4675757

Filename

4675757